Analysis and Optimization of Dynamic Spectrum Sharing for Cognitive Radio Networks

The goal of this dissertation is to present the analysis and optimization of dynamic spectrum sharing for cognitive radio networks (CRNs). Spectrum scarcity is a well known problem at present. In order to deal with this problem, dynamic spectrum sharing (DSS) was proposed. DSS is a technique where cognitive radio networks dynamically and opportunistically share the channels with primary users. The major contribution of this dissertation is in analyzing the problem of dynamic spectrum sharing under different scenarios and developing optimal solutions for these scenarios. In the first scenario, a contention based dynamic spectrum sharing model is considered and its throughput analysis is presented. One of the applications of this throughput analysis is in finding the optimal number of secondary users in such a scenario. The problem is studied for fixed and random allocation of channels to primary users while secondary users try to opportunistically use these channels. Primary users contend for the channels, and secondary users try to use the channels only when primary users are not using it. These secondary users themselves contend for the opportunistic usage. The numerical formulas developed for finding the optimal number of secondary users have been carefully analyzed with the solutions obtained using the throughput model directly and finding the optimal number of secondary users. These two match very closely with each other and hence provide simple numerical formulas to calculate the optimal number. The second scenario studied is based upon the idea of pre-knowledge of primary user activity. For instance, the active broadcasting periods of TV channels can be obtained from past measurements as the TV channels activities are approximately fixed. In this scenario, time spectrum block (TSB) allocation for DSS is studied. Optimal TSB allocation is considered to minimize the total interference of the system and hence maximize the overall throughput of the system of community networks. The results obtained using the proposed ABCD algorithm follow very closely with the optimal results. Thus the simple algorithm developed can be used for time spectrum block allocation in practical scenarios

Joint Cooperative Spectrum Sensing and MAC Protocol Design for Multi-channel Cognitive Radio Networks

In this paper, we propose a semi-distributed cooperative spectrum sen sing (SDCSS) and channel access framework for multi-channel cognitive radio networks (CRNs). In particular, we c onsider a SDCSS scheme where secondary users (SUs) perform sensing and exchange sensing outcomes with ea ch other to locate spectrum holes. In addition, we devise the p -persistent CSMA-based cognitive MAC protocol integrating the SDCSS to enable efficient spectrum sharing among SUs. We then perform throughput analysis and develop an algorithm to determine the spectrum sensing and access parameters to maximize the throughput for a given allocation of channel sensing sets. Moreover, we consider the spectrum sensing set optimization problem for SUs to maxim ize the overall system throughput. We present both exhaustive search and low-complexity greedy algorithms to determine the sensing sets for SUs and analyze their complexity. We also show how our design and analysis can be extended to consider reporting errors. Finally, extensive numerical results are presented to demonstrate the sig nificant performance gain of our optimized design framework with respect to non-optimized designs as well as the imp acts of different protocol parameters on the throughput performance.Comment: accepted for publication EURASIP Journal on Wireless Communications and Networking, 201